Significant progress has been made in understanding the brain mechanisms that underlie addiction in animal models. However, addiction in humans arises through a complex interplay between individual vulnerabilities and experiences, in turn modulated by social and cultural factors. Relating the basic neurobiology of addiction to the clinical complexity of this condition in the real world remains a challenge. Doing so is an important step in translating basic scientific advances to improve prevention, diagnosis, and treatment of addiction. This work will pursue this over-arching goal by exploring the neural mechanisms that mediate social influences in nicotine addiction, using a combination of behavioral, neuroimaging, and computational modelling techniques. Social stress is a common trigger of smoking behavior, and of relapse in smokers trying to quit. We have recently shown that in vulnerable individuals, even mild social stress can lead to measurable increases in dopamine release. We hypothesize that such a mechanism is also important in vulnerability to addiction, and will test that hypothesis with both behavioral and PET imaging studies in addicted and non-addicted smokers. The proposed work will focus on two regions of the brain that seem to play key roles in addiction: striatum and orbitofrontal cortex, and examine how behaviors mediated by these brain regions are influenced by the dopamine changes induced by a standardized social stressor. Orbitofrontal cortex may be a crucial mediator of maladaptive responses to social stress: this region appears to be important in inhibiting the compulsive behavior at the core of addiction, but it is also involved in the interpretation of subtle social-emotional information, and in the regulation of the stress response. As such, dysfunction of orbitofrontal cortex could be a common factor underlying several aspects of addiction vulnerability. This work will explore how common mechanisms may underlie both the social and reinforcement-learning functions of orbitofrontal cortex, through a combination of computational modeling and behavioral methods. This proposal arises from a new collaboration between investigators with complementary theoretical, methodological, and clinical expertise. It aims to develop a solid theoretical and experimental foundation for applying neurobiological findings to understand the real-life complexity of addictive behavior in humans.